It is conventionally known that an output image of an image forming apparatus (e.g., an inkjet printer) is inferior to a corresponding input image in sharpness because of deviation in ink impact position, bleeding of ink (mechanical dot gain), or optical blur (optical dot gain). In this case, if preliminarily acquiring frequency characteristic of the output image is feasible, the reduction in sharpness can be compensated by applying convolution processing (hereinafter, referred to as “sharpness recovery processing”) to the input image with a filter having an inverse characteristic.
However, it is also known that applying the sharpness recovery processing using the filter having the inverse characteristic to an input image of the image forming apparatus (e.g., the inkjet printer) causes a reduction of luminance in a high-frequency region.
According to a conventional technique discussed in PTL 1, the reduction in luminance can be suppressed by preliminarily measuring a luminance change amount before and after sharpness recovery processing and performing correction based on a change amount measured for each pixel of an input image.
Further, a method discussed in PTL 2 includes embedding a delta function in a digital image, processing the digital image through intermediate (e.g., sharpening, printing, and, scanning) processing, and extracting the delta function from the processed image. The method discussed in PTL 2 further includes estimating Modulation Transfer Function (MTF), as frequency characteristic, from the extracted delta function, to perform correction. When the filter used for sharpening (recovery) processing is a Wiener filter, it is feasible to maximize the signal to noise ratio in the sharpening processing by dividing the MTF by a sum of a square of MTF and a square of noise if noise characteristic of an intermediate processing apparatus is known beforehand.